Question 1

The logistic regression model is appropriate for predicting a dependent variable with 3 categories.

Accepted Answer

A) True 
 B)False

Question 2

Logistic regression is best suited for dependent variables that are ______.

Accepted Answer

A)  continuous 
B)  ordinal 
C)  nominal 
D)  dichotomous 
A)  continuous 
B)  ordinal 
C)  nominal 
D)  dichotomous

Question 3

The logistic probability distribution uses which distribution?

Accepted Answer

A)  t-distribution 
B)  logistic probability distribution 
C)  linear distribution 
D)  curve-linear distribution 
A)  t-distribution 
B)  logistic probability distribution 
C)  linear distribution 
D)  curve-linear distribution

Question 4

The odds of an event occurring is ______.

Accepted Answer

A)  the critical value based on the alpha level selected and the number of degrees of freedom 
B)  the probability of getting the observed results given the fitted regression coefficients 
C)  the probability of a dependent variable being a particular value 
D)  the ratio of a probability over its complement 
A)  the critical value based on the alpha level selected and the number of degrees of freedom 
B)  the probability of getting the observed results given the fitted regression coefficients 
C)  the probability of a dependent variable being a particular value 
D)  the ratio of a probability over its complement

Question 5

In logistic regression, estimating the probability of a binary event occurring is also called the ______.

Accepted Answer

A)  reciprocal of the probability of the dependent variable occurring 
B)  Bernoulli event of the dependent variable occurring 
C)  log of the odds of the dependent variable occurring 
D)  rate of change of the dependent variable occurring 
A)  reciprocal of the probability of the dependent variable occurring 
B)  Bernoulli event of the dependent variable occurring 
C)  log of the odds of the dependent variable occurring 
D)  rate of change of the dependent variable occurring

The logistic regression model is appropriate for predicting a dependent variable with 3 categories.

Logistic regression is best suited for dependent variables that are ______.

The logistic probability distribution uses which distribution?

The odds of an event occurring is ______.

In logistic regression, estimating the probability of a binary event occurring is also called the ______.

The Importance of Statistics in the Criminological Sciences or Why Do I Have to Learn This Stuff

Levels of Measurement and Aggregation

Data Visualization Techniques: Ways of Understanding Data Distributions

Measures of Central Tendency

Measures of Dispersion

Probability, Probability Distributions, and an Introduction to Inferential Statistics

Point Estimation and Confidence Intervals

From Estimation to Statistical Tests: Hypothesis Testing for One Population Mean and Proportion

Testing Hypotheses With Categorical Data

Hypothesis Tests Involving Two Population Means or Proportions

Hypothesis Involving Three or More Population Means: Analysis of Variance

Bivariate Correlation and Regression

Controlling for a Third Variable: Multiple OlS Regression

Filters

Exam 14: Regression Analysis With a Dichotomous Dependent Variable: Logit Models

The logistic regression model is appropriate for predicting a dependent variable with 3 categories.

Logistic regression is best suited for dependent variables that are ______.

The logistic probability distribution uses which distribution?

The odds of an event occurring is ______.

In logistic regression, estimating the probability of a binary event occurring is also called the ______.

The Importance of Statistics in the Criminological Sciences or Why Do I Have to Learn This Stuff

Levels of Measurement and Aggregation

Data Visualization Techniques: Ways of Understanding Data Distributions

Measures of Central Tendency

Measures of Dispersion

Probability, Probability Distributions, and an Introduction to Inferential Statistics

Point Estimation and Confidence Intervals

From Estimation to Statistical Tests: Hypothesis Testing for One Population Mean and Proportion

Testing Hypotheses With Categorical Data

Hypothesis Tests Involving Two Population Means or Proportions

Hypothesis Involving Three or More Population Means: Analysis of Variance

Bivariate Correlation and Regression

Controlling for a Third Variable: Multiple OlS Regression

Filters